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TU DelftA Machine Learning Approachto Fringe-Location IdentificationFiras Sawaf and Roger Groves ● FASIG - Photon 12 ● Durham ● September 2012

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Fringe LocationEdge detection

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Fringe LocationPre-filtering

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A Machine Learning ApproachFree online course

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A Machine Learning ApproachNeural networks

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A Machine Learning ApproachTraining

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A Machine Learning ApproachTesting, training set 99.9%

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A Machine Learning ApproachTesting, over-fitting

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A Machine Learning ApproachTesting, cross-validation set 89.9%

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A Machine Learning ApproachTesting, cross-validation set

MCC% = Threshold% * MCC

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A Machine Learning ApproachIntuition

• AA: Ability to Absorb

• AG: Ability to Generalise

• AIM: Absorption vs. Ideal Measure

• SAG: Spread of Absorption vs. Generalisation

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A Machine Learning ApproachPerformance - Large AIM, Small SAG

120,000 training examples, 200 nodes in hidden layer

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A Machine Learning ApproachPerformance - Medium AIM, Large SAG

30,000 training examples, 800 nodes in hidden layer

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A Machine Learning ApproachPerformance - Small AIM, Large SAG

30,000 training examples, 1600 nodes in hidden layer

15Challenge the future

A Machine Learning ApproachPerformance - Medium AIM, Medium SAG

120,000 training examples, 1600 nodes in hidden layer